Oncogene associated with human cancers and methods of use thereof

ABSTRACT

The present invention provides methods of treating cancer by inhibiting MECP2 and identifying cancers that will respond to therapy using MECP2 as a biomarker.

RELATED APPLICATIONS

This application is a national stage application filed under 35 U.S.C.§371, of International Application No. PCT/US14/43701, filed on Jun. 23,2014 which claims priority to and the benefit of U.S. provisionalapplication no. 61/792,336 filed Jun. 21, 2013, the contents of whichare hereby incorporated by reference in its entirety.

FIELD OF THE INVENTION

The present invention relates generally to the identification of MECP2as an oncogene, methods of using such MECP2 in determining the responseto therapy and treating cancer by inhibiting MECP2.

SUMMARY OF THE INVENTION

In various aspects the invention features methods of predicting whethera tumor will respond to a cancer therapy by determining whether MECP2 isamplified or overexpressed in the tumor. Amplification or overexpressionindicates the tumor will respond to therapy. The MECP2 is the MECP2 longisoform, the MECP2 short isoform or both. The cancer therapy is anepigenetic therapy such as a DNA methylation inhibitor or a histonedeacetylation (HDAC) inhibitor. DNA methylation inhibitors include forexample 5-azacytidine or decitabine. When the MECP2 long isoform isoverexpressed it indicates that the subject will respond to aphosphoinositide 3-kinase (PI3K) inhibitor. When the MECP2 short isoformis overexpressed it indicated that the subject will respond to a MAPkinase inhibitor.

In some aspects the cancer therapy is a MECP2 inhibitor such as anucleic acid that inhibits MECP2 expression or activity. A nucleic acidthat inhibits MECP2 expression or activity includes for example anucleic acid that is complementary to a MECP2 nucleic acid or fragmentthereof. The cancer therapy is a MEK inhibitor, a phosphoinositide3-kinase (PI3K) inhibitor, a c-myc inhibitor, or a tyrosine kinaseinhibitor.

Also included in the invention are methods of treating subject with atumor having an MECP2 amplification or overexpression of MCEP2 byadministering to the subject a MECP2 inhibitor, a DNA methylationinhibitor a histone deacetylation (HDAC) inhibitor, a MEK inhibitor, aphosphoinositide 3-kinase (PI3K) inhibitor, a c-myc inhibitor, atyrosine kinase inhibitor or any combination thereof. When the MECP2long isoform is overexpressed a subject is treated with a aphosphoinositide 3-kinase (PI3K) inhibitor. When the MECP2 short isoformis present the subject is treated with a MAP kinase inhibitor.

In a further aspect the invention provides a method of identifying agene capable of tumorigenic transformation by providing a primary cellculture transformed with three of the following genetic elements:telomerase; SV40 large-T antigen; SV40 small-T antigen or RAS andcontacting the cell culture with an expression library of humanprotein-coding sequences. Genes capable of tumorigenic transformationare identified by determining what human protein sequence when expressedin the cell allows for anchorage independent growth.

Unless otherwise defined, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention pertains. Although methods and materialssimilar or equivalent to those described herein can be used in thepractice of the present invention, suitable methods and materials aredescribed below. All publications, patent applications, patents, andother references mentioned herein are expressly incorporated byreference in their entirety. In cases of conflict, the presentspecification, including definitions, will control. In addition, thematerials, methods, and examples described herein are illustrative onlyand are not intended to be limiting.

Other features and advantages of the invention will be apparent from andencompassed by the following detailed description and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates the experimental transformation of primary cells.

FIG. 2 illustrates the screen according to the invention

FIG. 3 is a photograph of PCT amplification of cDNA inserts form softagar colonies.

FIG. 4 shows that MECP2 causes anchorage independent growth in n-RAScells.

FIG. 5 summarizes the functions of MECP2.

FIG. 6 illustrates MECP2 protein interactions.

FIG. 7 summarizes MECP2 amplifications in cancer.

FIG. 8 shows MECP2 amplification in gynecological cancers.

FIG. 9 shows MEPC2 expression in breast cancers.

FIG. 10 shows MEPC2 expression in ovarian cell lines

FIG. 11 shows MEPC2 expression in non-small cell lung cancer cell lines.

FIG. 12 illustrates the effect of loss of function point mutation intransformation potential of MECP2.

FIG. 13 shows that MECP2 partially rescues cytotoxic andanti-proliferative effects of RAS suppression in a human tumor cell line

FIG. 14 shows that MECP2 activates MAP kinase pathway.

FIG. 15 illustrates that mutation in MECP2 that fail to transform alsodo not activate MAPK pathway

FIG. 16 shows response to MEK inhibitors.

FIG. 17 illustrates that some breast tumor lines depend on MECP2 forgrowth.

FIG. 18 illustrates that some lung tumor lines depend on MECP2 forgrowth.

FIG. 19 illustrates that some MECP2 is required for growth in MEPC2overexpressing cancer cell lines.

FIG. 20 shows that epigenetic therapies are effective in MECP2-relatedcancers

FIG. 21 illustrates the synergistic effect of 5-asacytidine and TSA.

FIG. 22 shows MECP2 expression in triple negative breast cancer (TNBC)patient derived xenografts. MDAMB453 and MDAMB2311 are positive andnegative controls for MECP2 overexpression respectively. The remainingsamples are patient-derived xenografts (PDXs). PDXs 12-19, 13-13, 13-11and 13-47 overexpress MECP2.

FIG. 23 shows that MECP2 splicing isoforms activate distinct growthfactor pathways. hMEC cells contains sv40 small t, SV40 large T, hTERT,and infected with lentiviruses expressing the indicated genes werebriefly deprived of growth factors, and lysates prepared were subjectedto western blot and probed with the antibodies indicated on the right.

FIG. 24 shows that MECP2 overexpressing TNBC cells are addicted tocontinued MECP2 expression. MECP2 overexpressing TNBC cell lines BT549and MDA-MB468 and MECP2 non-overexpressing cell lines ZR75-1 wereinfected with vectors encoding two different shRNA to MECP2 orLuciferase as a control. Crystal violet staining was done several dayslater and quantitated by OD595.

DETAILED DESCRIPTION OF THE INVENTION

The present invention relates to the identification of Methyl CpGbinding protein 2 (MECP2) as an oncogene. MECP2 is amplified in a numberof human cancers such as ovarian cancer and lung adenocarcinomas.Suppression of MECP2 expression significantly inhibits proliferation inseveral human tumor cell lines that naturally overexpress MECP2, butdoes not inhibit proliferation of tumor cell lines that do notoverexpress MECP2.

The MECP2 gene expresses two splicing isoforms that differ by inclusionof the second exon, resulting in a long isoform that consists of 21unique amino acids at the amino terminus followed by a 477 amino acidshared region, and a short isoform that has 9 unique amino acids at theamino terminus attached to the same 477aa shared region.

Human cancers harbor innumerable genetic and epigenetic alterationspresenting formidable challenges in deciphering those changes that drivethe malignant process and dictate a given tumor's clinical behavior. Theneed for accurately predictive biomarkers reflective of a tumor'sresponse to therapy is evident across many cancer types,

Primary human mammary epithelial cells were transformed with three ofthe four genetic elements of a transformation cocktail (telomerase,SV-40 large T-antigen, SV-40 call T-antigen and RAS) that are requiredto convert normal primary human cells into tumorigenic cells. Withoutthe fourth component of the transformation cocktail the cells will notgrow on soft agar. The lentiviral expression library having about 17,000different human protein-coding sequences was then inserted into thesecells and the cells were plated on soft agar. Genes that couldsubstitute for the fourth component were by identified by isolation ofthe transduced cDNAs for cell colonies that grew in soft agar. Usingthis system MECP2 was identified as being sufficient to substitute foractivated RAS for tumorgenesis.

As MCEP2 is overexpressed in many human cancers it was hypothesized thatMECP2 expression on its own may have the capacity to promote tumor cellproliferation. To test this hypothesis, MECP2 expression was suppressedusing shRNA. Suppression of MECP2 expression significantly inhibitedproliferation in tumor cells lines that over express MECP2 but not incells that do not overexpress MECP2. These findings indicate that MCEP2promote tumor growth.

In addition, these results indicate MECP2 is useful as therapeutictargets for treating MECP2 expressing tumors.

Predicting the Response to Therapy

MECP2 expression is also useful for monitoring subjects undergoingtreatments and therapies for cancer, and for selecting or modifyingtherapies and treatments that would be efficacious in subjects havingcancer. The selection and use of such treatments and therapies slows theprogression of the tumor, or substantially delays or prevent its onset,or reduces or prevents the incidence of tumor metastasis. In addition,MECP2 is useful as a therapeutic target for treating MECP2 expressingtumors.

The methods disclosed herein are used with subjects undergoing treatmentand/or therapies for cancer, subjects who are at risk for developing areoccurrence of a cancer, and subjects who have been diagnosed with acancer. The methods of the present invention are to be used to monitoror select a treatment regimen for a subject who has a cancer.

Specifically, the invention provides methods of determining theresponsiveness, e.g., sensitivity or resistance, of an individual'stumor therapy. More specifically, the invention provides methods ofdetermining whether a patient with a cancer will be responsive to MECP2inhibitor therapy by determining whether MECP2 is overexpressed and/oramplified in the tumor. Overexpression and/or amplification of MECP2indicates that the tumor will be responsive to MECP2 inhibitor therapy.The MECP2 that is overexpressed is the MECP2 long isoform, the MECP2short isoform or both.

By MECP2 inhibitor therapy it is meant any compound that inhibits theexpression or activity of MECP2 such as a nucleic acids that arecomplementary to a MECP2 nucleic acid, and also included are epigenetictherapies such inhibiting DNA methylation or histone deacetylation.MECP2 inhibitor therapy also includes inhibition of themitogen-activated protein kinase pathway (MAP2K), tyrosine kinase; c-mycor phosphoinositide 3-kinase (PI3K).

Furthermore, the MECP2 gene expresses two splicing isoforms. The twosplicing isoforms can activate different cellular signaling pathways asshown below in Example 1. Expression of the differing isoforms mayprovide an indication of which MECP2 inhibition therapy is likely tosucceed. For example, overexpression of the MECP2 short isoform may bestrespond to treatment by inhibition of the MAP kinase pathway, whereasoverexpression of the MECP2 long isoform may best respond to inhibitionof the PI3K pathway.

These methods are both a positive and negative predictive test and thusallow clinicians to better focus the use of these expensive and toxicagents to that subset of the population with the greatest potentialchance of benefit as early as possible.

Methods of Treating Cancer

The invention provides methods of treating or alleviating a symptom ofcancer by administering to s subject in need thereof a MECP2 inhibitor.

A MECP2 inhibitor is a compound that decreases expression or activity ofMECP2.

A decrease in MECP2 expression or activity is defined by a reduction ofa biological function of the MECP2. A biological function of MCP2includes binding to methylated DNA.

MECP2 expression is measured by detecting a MECP2 transcript or protein.MECP2 inhibitors are known in the art or are identified using methodsdescribed herein.

The MECP2 inhibitor can be a small molecule. A “small molecule” as usedherein, is meant to refer to a composition that has a molecular weightin the range of less than about 5 kD to 50 daltons, for example lessthan about 4 kD, less than about 3.5 kD, less than about 3 kD, less thanabout 2.5 kD, less than about 2 kD, less than about 1.5 kD, less thanabout 1 kD, less than 750 daltons, less than 500 daltons, less thanabout 450 daltons, less than about 400 daltons, less than about 350daltons, less than 300 daltons, less than 250 daltons, less than about200 daltons, less than about 150 daltons, less than about 100 daltons.Small molecules can be, e.g., nucleic acids, peptides, polypeptides,peptidomimetics, carbohydrates, lipids or other organic or inorganicmolecules. Libraries of chemical and/or biological mixtures, such asfungal, bacterial, or algal extracts, are known in the art and can bescreened with any of the assays of the invention.

The MECP2 inhibitor is an antibody or fragment thereof specific toMECP2.

Alternatively, the MECP2 inhibitor is for example an antisense MECP2nucleic acid, a MECP2-specific short-interfering RNA, or aMECP2-specific ribozyme. By the term “siRNA” is meant a double strandedRNA molecule which prevents translation of a target mRNA. Standardtechniques of introducing siRNA into a cell are used, including those inwhich DNA is a template from which an siRNA is transcribed. The siRNAincludes a sense MECP2 nucleic acid sequence, an anti-sense MECP2nucleic acid sequence or both. Optionally, the siRNA is constructed suchthat a single transcript has both the sense and complementary antisensesequences from the target gene, e.g., a hairpin.

Binding of the siRNA to a MECP2 transcript in the target cell results ina reduction in MECP2 production by the cell. The length of theoligonucleotide is at least 10 nucleotides and may be as long as thenaturally-occurring MECP2 transcript. Preferably, the oligonucleotide is19-25 nucleotides in length. Most preferably, the oligonucleotide isless than 75, 50, 25 nucleotides in length.

Exemplary MECP2 inhibitors include for example a DNA methylationinhibitor (e.g., 5-azacytidine or decitabine), a histone deacetylation(HDAC) inhibitor; a MEK inhibitor, a phosphoinositide 3-kinase (PI3K)inhibitor, a c-myc inhibitor, or a tyrosine kinase inhibitor.

In particular embodiment when the MECP2 short isoform is overexpressedpreferred MECP2 inhibitors are MAP kinase inhibitors. In otherembodiments when the MECP2 long isoform is overexpressed preferred MECP2inhibitors are phosphoinositide 3-kinase (PI3K) inhibitors.

The growth of tumor cells is inhibited, e.g. reduced, by contacting aMECP2 overexpressing tumor cell with a composition containing a compoundthat decreases the expression or activity of MECP2. By inhibition ofcell growth is meant the cell proliferates at a lower rate or hasdecreased viability compared to a cell not exposed to the composition.Cell growth is measured by methods known in the art such as, the MTTcell proliferation assay, cell counting, measurement of ATP content,crystal violet staining, or measurement of total GFP from GFP expressingcell lines.

Cells are directly contacted with the compound. Alternatively, thecompound is administered systemically.

The methods are useful to alleviate the symptoms of a variety ofcancers. Any cancer exhibiting MECP2 overexpression or amplification isamenable to treatment by the methods of the invention.

Treatment is efficacious if the treatment leads to clinical benefit suchas, a decrease in size, prevalence, or metastatic potential of the tumorin the subject. When treatment is applied prophylactically,“efficacious” means that the treatment retards or prevents tumors fromforming or prevents or alleviates a symptom of clinical symptom of thetumor. Efficacy is determined in association with any known method fordiagnosing or treating the particular tumor type.

Therapeutic Administration

The invention includes administering to a subject composition comprisinga MECP2 inhibitor.

An effective amount of a therapeutic compound is preferably from about0.1 mg/kg to about 150 mg/kg. Effective doses vary, as recognized bythose skilled in the art, depending on route of administration,excipient usage, and coadministration with other therapeutic treatmentsincluding use of other anti-proliferative agents or therapeutic agentsfor treating, preventing or alleviating a symptom of a cancer. Atherapeutic regimen is carried out by identifying a mammal, e.g., ahuman patient suffering from a cancer using standard methods.

The pharmaceutical compound is administered to such an individual usingmethods known in the art. Preferably, the compound is administeredorally, rectally, nasally, topically or parenterally, e.g.,subcutaneously, intraperitoneally, intramuscularly, and intravenously.The inhibitors are optionally formulated as a component of a cocktail oftherapeutic drugs to treat cancers. Examples of formulations suitablefor parenteral administration include aqueous solutions of the activeagent in an isotonic saline solution, a 5% glucose solution, or anotherstandard pharmaceutically acceptable excipient. Standard solubilizingagents such as PVP or cyclodextrins are also utilized as pharmaceuticalexcipients for delivery of the therapeutic compounds.

The therapeutic compounds described herein are formulated intocompositions for other routes of administration utilizing conventionalmethods. For example, the therapeutic compounds are formulated in acapsule or a tablet for oral administration. Capsules may contain anystandard pharmaceutically acceptable materials such as gelatin orcellulose. Tablets may be formulated in accordance with conventionalprocedures by compressing mixtures of a therapeutic compound with asolid carrier and a lubricant. Examples of solid carriers include starchand sugar bentonite. The compound is administered in the form of a hardshell tablet or a capsule containing a binder, e.g., lactose ormannitol, conventional filler, and a tableting agent. Other formulationsinclude an ointment, suppository, paste, spray, patch, cream, gel,resorbable sponge, or foam. Such formulations are produced using methodswell known in the art.

Therapeutic compounds are effective upon direct contact of the compoundwith the affected tissue. Accordingly, the compound is administeredtopically. Alternatively, the therapeutic compounds are administeredsystemically. For example, the compounds are administered by inhalation.The compounds are delivered in the form of an aerosol spray frompressured container or dispenser which contains a suitable propellant,e.g., a gas such as carbon dioxide, or a nebulizer.

Additionally, compounds are administered by implanting (either directlyinto an organ or subcutaneously) a solid or resorbable matrix whichslowly releases the compound into adjacent and surrounding tissues ofthe subject.

Screening Assays

The invention also provides a method of screening for therapeutictargets (i.e. genes capable of tumorigenic transformation) for treatingcancers. In particular, the invention provides a method for identifyingtherapeutic targets for treating cancer by providing primary cellculture transformed with three of the following genetic elements:telomerase; SV40 large-T antigen; SV40 small-T antigen or RAS andcontacting the cell with a library of human protein sequences. Potentialtherapeutic targets are identified by determining what human proteinsequence when expressed in the cell allows for anchorage independentgrowth.

Performance and Accuracy Measures of the Invention

The performance and thus absolute and relative clinical usefulness ofthe invention may be assessed in multiple ways as noted above. Amongstthe various assessments of performance, the invention is intended toprovide accuracy in clinical diagnosis and prognosis. The accuracy of adiagnostic, predictive, or prognostic test, assay, or method concernsthe ability of the test, assay, or method to distinguish betweensubjects responsive to chemotherapeutic treatment and those that arenot, is based on whether the subjects has an amplification oroverexpression of MECP2.

In the categorical diagnosis of a disease state, changing the cut pointor threshold value of a test (or assay) usually changes the sensitivityand specificity, but in a qualitatively inverse relationship. Therefore,in assessing the accuracy and usefulness of a proposed medical test,assay, or method for assessing a subject's condition, one should alwaystake both sensitivity and specificity into account and be mindful ofwhat the cut point is at which the sensitivity and specificity are beingreported because sensitivity and specificity may vary significantly overthe range of cut points. Use of statistics such as AUC, encompassing allpotential cut point values, is preferred for most categorical riskmeasures using the invention, while for continuous risk measures,statistics of goodness-of-fit and calibration to observed results orother gold standards, are preferred.

Using such statistics, an “acceptable degree of diagnostic accuracy”, isherein defined as a test or assay in which the AUC (area under the ROCcurve for the test or assay) is at least 0.60, desirably at least 0.65,more desirably at least 0.70, preferably at least 0.75, more preferablyat least 0.80, and most preferably at least 0.85.

By a “very high degree of diagnostic accuracy”, it is meant a test orassay in which the AUC (area under the ROC curve for the test or assay)is at least 0.80, desirably at least 0.85, more desirably at least0.875, preferably at least 0.90, more preferably at least 0.925, andmost preferably at least 0.95.

The predictive value of any test depends on the sensitivity andspecificity of the test, and on the prevalence of the condition in thepopulation being tested. This notion, based on Bayes' theorem, providesthat the greater the likelihood that the condition being screened for ispresent in an individual or in the population (pre-test probability),the greater the validity of a positive test and the greater thelikelihood that the result is a true positive. Thus, the problem withusing a test in any population where there is a low likelihood of thecondition being present is that a positive result has limited value(i.e., more likely to be a false positive). Similarly, in populations atvery high risk, a negative test result is more likely to be a falsenegative.

As a result, ROC and AUC can be misleading as to the clinical utility ofa test in low disease prevalence tested populations (defined as thosewith less than 1% rate of occurrences (incidence) per annum, or lessthan 10% cumulative prevalence over a specified time horizon).Alternatively, absolute risk and relative risk ratios as definedelsewhere in this disclosure can be employed to determine the degree ofclinical utility. Populations of subjects to be tested can also becategorized into quartiles by the test's measurement values, where thetop quartile (25% of the population) comprises the group of subjectswith the highest relative risk for therapeutic unresponsiveness, and thebottom quartile comprising the group of subjects having the lowestrelative risk for therapeutic unresponsiveness. Generally, valuesderived from tests or assays having over 2.5 times the relative riskfrom top to bottom quartile in a low prevalence population areconsidered to have a “high degree of diagnostic accuracy,” and thosewith five to seven times the relative risk for each quartile areconsidered to have a “very high degree of diagnostic accuracy.”Nonetheless, values derived from tests or assays having only 1.2 to 2.5times the relative risk for each quartile remain clinically useful arewidely used as risk factors for a disease; such is the case with totalcholesterol and for many inflammatory biomarkers with respect to theirprediction of future events. Often such lower diagnostic accuracy testsmust be combined with additional parameters in order to derivemeaningful clinical thresholds for therapeutic intervention, as is donewith the aforementioned global risk assessment indices.

A health economic utility function is yet another means of measuring theperformance and clinical value of a given test, consisting of weightingthe potential categorical test outcomes based on actual measures ofclinical and economic value for each. Health economic performance isclosely related to accuracy, as a health economic utility functionspecifically assigns an economic value for the benefits of correctclassification and the costs of misclassification of tested subjects. Asa performance measure, it is not unusual to require a test to achieve alevel of performance which results in an increase in health economicvalue per test (prior to testing costs) in excess of the target price ofthe test.

In general, alternative methods of determining diagnostic accuracy arecommonly used for continuous measures, when a disease category or riskcategory has not yet been clearly defined by the relevant medicalsocieties and practice of medicine, where thresholds for therapeutic useare not yet established, or where there is no existing gold standard fordiagnosis of the pre-disease. For continuous measures of risk, measuresof diagnostic accuracy for a calculated index are typically based oncurve fit and calibration between the predicted continuous value and theactual observed values (or a historical index calculated value) andutilize measures such as R squared, Hosmer-Lemeshow P-value statisticsand confidence intervals. It is not unusual for predicted values usingsuch algorithms to be reported including a confidence interval (usually90% or 95% CI) based on a historical observed cohort's predictions, asin the test for risk of future breast cancer recurrence commercializedby Genomic Health, Inc. (Redwood City, Calif.).

Definitions

“Accuracy” refers to the degree of conformity of a measured orcalculated quantity (a test reported value) to its actual (or true)value. Clinical accuracy relates to the proportion of true outcomes(true positives (TP) or true negatives (TN) versus misclassifiedoutcomes (false positives (FP) or false negatives (FN)), and may bestated as a sensitivity, specificity, positive predictive values (PPV)or negative predictive values (NPV), or as a likelihood, odds ratio,among other measures.

“Biomarker” in the context of the present invention encompasses, withoutlimitation, proteins, nucleic acids, and metabolites, together withtheir polymorphisms, mutations, variants, modifications, subunits,fragments, protein-ligand complexes, and degradation products,protein-ligand complexes, elements, related metabolites, and otheranalytes or sample-derived measures. Biomarkers can also include mutatedproteins or mutated nucleic acids. Biomarkers also encompass non-bloodborne factors or non-analyte physiological markers of health status,such as “clinical parameters” defined herein, as well as “traditionallaboratory risk factors”, also defined herein. Biomarkers also includeany calculated indices created mathematically or combinations of any oneor more of the foregoing measurements, including temporal trends anddifferences. Where available, and unless otherwise described herein,biomarkers which are gene products are identified based on the officialletter abbreviation or gene symbol assigned by the international HumanGenome Organization Naming Committee (HGNC) and listed at the date ofthis filing at the US National Center for Biotechnology Information(NCBI) web site.

A “Clinical indicator” is any physiological datum used alone or inconjunction with other data in evaluating the physiological condition ofa collection of cells or of an organism. This term includes pre-clinicalindicators.

“Clinical parameters” encompasses all non-sample or non-analytebiomarkers of subject health status or other characteristics, such as,without limitation, age (Age), ethnicity (RACE), gender (Sex), or familyhistory (FamHX).

“FN” is false negative, which for a disease state test means classifyinga disease subject incorrectly as non-disease or normal.

“FP” is false positive, which for a disease state test means classifyinga normal subject incorrectly as having disease.

A “formula,” “algorithm,” or “model” is any mathematical equation,algorithmic, analytical or programmed process, or statistical techniquethat takes one or more continuous or categorical inputs (herein called“parameters”) and calculates an output value, sometimes referred to asan “index” or “index value.” Non-limiting examples of “formulas” includesums, ratios, and regression operators, such as coefficients orexponents, biomarker value transformations and normalizations(including, without limitation, those normalization schemes based onclinical parameters, such as gender, age, or ethnicity), rules andguidelines, statistical classification models, and neural networkstrained on historical populations. Of particular use in combiningbiomarkers are linear and non-linear equations and statisticalclassification analyses to determine the relationship between biomarkersdetected in a subject sample and the subject's responsiveness tochemotherapy. In panel and combination construction, of particularinterest are structural and synactic statistical classificationalgorithms, and methods of risk index construction, utilizing patternrecognition features, including established techniques such ascross-correlation, Principal Components Analysis (PCA), factor rotation,Logistic Regression (LogReg), Linear Discriminant Analysis (LDA),Eigengene Linear Discriminant Analysis (ELDA), Support Vector Machines(SVM), Random Forest (RF), Recursive Partitioning Tree (RPART), as wellas other related decision tree classification techniques, ShrunkenCentroids (SC), StepAIC, Kth-Nearest Neighbor, Boosting, Decision Trees,Neural Networks, Bayesian Networks, Support Vector Machines, and HiddenMarkov Models, among others. Other techniques may be used in survivaland time to event hazard analysis, including Cox, Weibull, Kaplan-Meierand Greenwood models well known to those of skill in the art. Many ofthese techniques are useful as forward selection, backwards selection,or stepwise selection, complete enumeration of all potential panels of agiven size, genetic algorithms, or they may themselves include biomarkerselection methodologies in their own technique. These may be coupledwith information criteria, such as Akaike's Information Criterion (AIC)or Bayes Information Criterion (BIC), in order to quantify the tradeoffbetween additional biomarkers and model improvement, and to aid inminimizing overfit. The resulting predictive models may be validated inother studies, or cross-validated in the study they were originallytrained in, using such techniques as Bootstrap, Leave-One-Out (LOO) and10-Fold cross-validation (10-Fold CV). At various steps, false discoveryrates may be estimated by value permutation according to techniquesknown in the art. A “health economic utility function” is a formula thatis derived from a combination of the expected probability of a range ofclinical outcomes in an idealized applicable patient population, bothbefore and after the introduction of a diagnostic or therapeuticintervention into the standard of care. It encompasses estimates of theaccuracy, effectiveness and performance characteristics of suchintervention, and a cost and/or value measurement (a utility) associatedwith each outcome, which may be derived from actual health system costsof care (services, supplies, devices and drugs, etc.) and/or as anestimated acceptable value per quality adjusted life year (QALY)resulting in each outcome. The sum, across all predicted outcomes, ofthe product of the predicted population size for an outcome multipliedby the respective outcomes expected utility is the total health economicutility of a given standard of care. The difference between (i) thetotal health economic utility calculated for the standard of care withthe intervention versus (ii) the total health economic utility for thestandard of care without the intervention results in an overall measureof the health economic cost or value of the intervention. This mayitself be divided amongst the entire patient group being analyzed (orsolely amongst the intervention group) to arrive at a cost per unitintervention, and to guide such decisions as market positioning,pricing, and assumptions of health system acceptance. Such healtheconomic utility functions are commonly used to compare thecost-effectiveness of the intervention, but may also be transformed toestimate the acceptable value per QALY the health care system is willingto pay, or the acceptable cost-effective clinical performancecharacteristics required of a new intervention.

For diagnostic (or prognostic) interventions of the invention, as eachoutcome (which in a disease classifying diagnostic test may be a TP, FP,TN, or FN) bears a different cost, a health economic utility functionmay preferentially favor sensitivity over specificity, or PPV over NPVbased on the clinical situation and individual outcome costs and value,and thus provides another measure of health economic performance andvalue which may be different from more direct clinical or analyticalperformance measures. These different measurements and relativetrade-offs generally will converge only in the case of a perfect test,with zero error rate (a.k.a., zero predicted subject outcomemisclassifications or FP and FN), which all performance measures willfavor over imperfection, but to differing degrees.

“Measuring” or “measurement,” or alternatively “detecting” or“detection,” means assessing the presence, absence, quantity or amount(which can be an effective amount) of either a given substance within aclinical or subject-derived sample, including the derivation ofqualitative or quantitative concentration levels of such substances, orotherwise evaluating the values or categorization of a subject'snon-analyte clinical parameters.

“Negative predictive value” or “NPV” is calculated by TN/(TN+FN) or thetrue negative fraction of all negative test results. It also isinherently impacted by the prevalence of the disease and pre-testprobability of the population intended to be tested.

See, e.g., O′Marcaigh A S, Jacobson R M, “Estimating The PredictiveValue Of A Diagnostic Test, How To Prevent Misleading Or ConfusingResults,” Clin. Ped. 1993, 32(8): 485-491, which discusses specificity,sensitivity, and positive and negative predictive values of a test,e.g., a clinical diagnostic test. Often, for binary disease stateclassification approaches using a continuous diagnostic testmeasurement, the sensitivity and specificity is summarized by ReceiverOperating Characteristics (ROC) curves according to Pepe et al,“Limitations of the Odds Ratio in Gauging the Performance of aDiagnostic, Prognostic, or Screening Marker,” Am. J. Epidemiol 2004, 159(9): 882-890, and summarized by the Area Under the Curve (AUC) orc-statistic, an indicator that allows representation of the sensitivityand specificity of a test, assay, or method over the entire range oftest (or assay) cut points with just a single value. See also, e.g.,Shultz, “Clinical Interpretation Of Laboratory Procedures,” chapter 14in Teitz, Fundamentals of Clinical Chemistry, Burtis and Ashwood (eds.),4th edition 1996, W.B. Saunders Company, pages 192-199; and Zweig etal., “ROC Curve Analysis: An Example Showing The Relationships AmongSerum Lipid And Apolipoprotein Concentrations In Identifying SubjectsWith Coronory Artery Disease,” Clin. Chem., 1992, 38(8): 1425-1428. Analternative approach using likelihood functions, odds ratios,information theory, predictive values, calibration (includinggoodness-of-fit), and reclassification measurements is summarizedaccording to Cook, “Use and Misuse of the Receiver OperatingCharacteristic Curve in Risk Prediction,” Circulation 2007, 115:928-935.

Finally, hazard ratios and absolute and relative risk ratios withinsubject cohorts defined by a test are a further measurement of clinicalaccuracy and utility. Multiple methods are frequently used to definingabnormal or disease values, including reference limits, discriminationlimits, and risk thresholds.

“Analytical accuracy” refers to the reproducibility and predictabilityof the measurement process itself, and may be summarized in suchmeasurements as coefficients of variation, and tests of concordance andcalibration of the same samples or controls with different times, users,equipment and/or reagents. These and other considerations in evaluatingnew biomarkers are also summarized in Vasan, 2006.

“Performance” is a term that relates to the overall usefulness andquality of a diagnostic or prognostic test, including, among others,clinical and analytical accuracy, other analytical and processcharacteristics, such as use characteristics (e.g., stability, ease ofuse), health economic value, and relative costs of components of thetest. Any of these factors may be the source of superior performance andthus usefulness of the test, and may be measured by appropriate“performance metrics,” such as AUC, time to result, shelf life, etc. asrelevant.

“Positive predictive value” or “PPV” is calculated by TP/(TP+FP) or thetrue positive fraction of all positive test results. It is inherentlyimpacted by the prevalence of the disease and pre-test probability ofthe population intended to be tested.

“Risk” in the context of the present invention, relates to theprobability that an event will occur over a specific time period, as inthe responsiveness to treatment, cancer recurrence or survival and canmean a subject's “absolute” risk or “relative” risk. Absolute risk canbe measured with reference to either actual observation post-measurementfor the relevant time cohort, or with reference to index valuesdeveloped from statistically valid historical cohorts that have beenfollowed for the relevant time period. Relative risk refers to the ratioof absolute risks of a subject compared either to the absolute risks oflow risk cohorts or an average population risk, which can vary by howclinical risk factors are assessed. Odds ratios, the proportion ofpositive events to negative events for a given test result, are alsocommonly used (odds are according to the formula p/(1−p) where p is theprobability of event and (1−p) is the probability of no event) tono-conversion.

“Risk evaluation” or “evaluation of risk” in the context of the presentinvention encompasses making a prediction of the probability, odds, orlikelihood that an event or disease state may occur, the rate ofoccurrence of the event or conversion from one disease state. Riskevaluation can also comprise prediction of future clinical parameters,traditional laboratory risk factor values, or other indices of cancer,either in absolute or relative terms in reference to a previouslymeasured population. The methods of the present invention may be used tomake continuous or categorical measurements of the responsiveness totreatment thus diagnosing and defining the risk spectrum of a categoryof subjects defined as being responders or non-responders. In thecategorical scenario, the invention can be used to discriminate betweennormal and other subject cohorts at higher risk for responding. Suchdiffering use may require different biomarker combinations andindividualized panels, mathematical algorithms, and/or cut-off points,but be subject to the same aforementioned measurements of accuracy andperformance for the respective intended use.

A “sample” in the context of the present invention is a biologicalsample isolated from a subject and can include, by way of example andnot limitation, tissue biopsies, whole blood, serum, plasma, bloodcells, endothelial cells, lymphatic fluid, ascites fluid, interstitialfluid (also known as “extracellular fluid” and encompasses the fluidfound in spaces between cells, including, inter alia, gingivalcrevicular fluid), bone marrow, cerebrospinal fluid (CSF), saliva,mucous, sputum, sweat, urine, or any other secretion, excretion, orother bodily fluids. A “sample” may include a single cell or multiplecells or fragments of cells. The sample is also a tissue sample. Thesample is or contains a circulating endothelial cell or a circulatingtumor cell. The sample includes a primary tumor cell, primary tumor, arecurrent tumor cell, or a metastatic tumor cell.

“Sensitivity” is calculated by TP/(TP+FN) or the true positive fractionof disease subjects.

“Specificity” is calculated by TN/(TN+FP) or the true negative fractionof non-disease or normal subjects.

By “statistically significant”, it is meant that the alteration isgreater than what might be expected to happen by chance alone (whichcould be a “false positive”). Statistical significance can be determinedby any method known in the art. Commonly used measures of significanceinclude the p-value, which presents the probability of obtaining aresult at least as extreme as a given data point, assuming the datapoint was the result of chance alone. A result is considered highlysignificant at a p-value of 0.05 or less. Preferably, the p-value is0.04, 0.03, 0.02, 0.01, 0.005, 0.001 or less.

A “subject” in the context of the present invention is preferably amammal. The mammal can be a human, non-human primate, mouse, rat, dog,cat, horse, or cow, but are not limited to these examples. Mammals otherthan humans can be advantageously used as subjects that represent animalmodels of cancer. A subject can be male or female.

“TN” is true negative, which for a disease state test means classifyinga non-disease or normal subject correctly.

“TP” is true positive, which for a disease state test means correctlyclassifying a disease subject.

“Traditional laboratory risk factors” correspond to biomarkers isolatedor derived from subject samples and which are currently evaluated in theclinical laboratory and used in traditional global risk assessmentalgorithms. Traditional laboratory risk factors for tumor recurrenceinclude for example Proliferative index, tumor infiltrating lymphocytes.Other traditional laboratory risk factors for tumor recurrence known tothose skilled in the art.

EXAMPLE 1 Initial Characterization of MECP2 as a New Oncogene

The MECP2 short splicing isoform enables the soft agar growth of primarybreast epithelial cells containing introduced SV40 large-T, SV40small-T, and hTERT with about the same efficiency as activated RAS (FIG.4A). To assess the potential relevance of MECP2 across all humancancers, a query was made of TCGA copy number data through the BroadInstitute TCGA copy number portal. MECP2 is amplified with extremelyhigh statistical significance across all human cancers (FIG. 8) (Q value7.7×10⁻¹⁸; Q less than 0.25 signifies likelihood that the gene inquestion is amplified above the background rate in the genome and thatamplifications at this locus are enriched by selective pressure). MECP2is significantly amplified in a number of individual human cancer types,and is amplified at particularly high frequencies in women's cancers(see FIG. 8).

EXAMPLE 2 Signaling Pathways Activated by MECP2 Splicing Isoforms

To ascertain if MECP2 overexpression recapitulates signal transductionevents seen with activated RAS, signaling pathways downstream of RASwere analyzed in N-RAS hMEC cells expressing MECP2 isoforms. The MECP2gene expresses two splicing isoforms that differ by inclusion of thesecond exon resulting in a long isoform that consists of 21 unique aminoacids at the amino terminus followed by a 477 amino acid shared region,and a short isoform that has 9 unique amino acids at the amino terminusattached to the same 477 amino acid shared region. In most cancers, thathave MECP2 amplification, the expression of both isoforms is increased.

It has been shown that, like activated RAS, overexpression of the MECP2short isoform causes ERK1/2 phosphorylation (see FIG. 23A), while theMECP2 long isoform activates the PI3K pathway, as monitored by theconcentration of phosphorylated AKT (see FIG. 23B). These growth factorpathway activation events were blocked by the presence of mutations inthe MECP2 methylated DNA binding region. Supporting the importance ofthe MAPK pathway, it was demonstrated that two MEK inhibitors withdifferent mechanisms of action significantly slowed the growth of MECP2transformed cells.

Therefore, in at least one cell type, human mammary epithelial cells,MECP2 short isoform can substitute for activated RAS to confer anchorageindependent growth upon human mammary epithelial cells that express theSV40 large-T, SV40 small-t, and hTERT. The MECP2 short isoform includesthe MAP kinase pathway to the same extent as activated RAS (see FIG.23A). The MECP2 short isoform rescues growth of tumor cells addicted toactivated RAS after shRNA suppression of RAS. The MECP2 long isoformactivates the PI3K pathway (see FIG. 23B).

EXAMPLE 3 MECP2 Causes Tumors in Nude Mice

N-RAS hMECs or N-RAS BPECs do not form tumors in nude mice. It has beenshown that in N-RAS hMECs, the combination of both the short and longMECP2 isoforms allow growth as xenografts in nude mice, while eachisoform individually does not. BEPCs are intrinsically 1000× moretumorigenic when transformed with SV40LT, st, hTERT and activated RAScompared with hMECs; in N-RAS BPECs, either the long or short isoform ofMECP2 is sufficient to cause tumors in nude mice, and the combination ofboth isoforms gives a higher percentage of tumor takes, and the tumorscause by the combination grow more rapidly than those caused by eitherisoform alone.

EXAMPLE 4 MECP2 as a Therapeutic Target

In a small survey, it was shown that several TNBC cell lines thatoverexpress MECP2 require continued MECP2 expression for growth(“oncogene addiction”, see FIG. 24) suggesting that MECP2 is a validtherapeutic target in TNBC. These MECP2-overexpressing TNBC lines, BT549and MDA-MB468, show highly significant growth inhibition when treatedwith any of three shRNAs (two of which are shown in FIG. 24) directedagainst MECP2, but not with control shRNA. Breast cancer lines that donot express high levels of MECP2, for example ZR75.1 (see FIG. 9) arenot inhibited by these shRNAs suggesting that off-target effects do notcause the growth inhibition observed.

It has been shown that human cancer lines derived from non-small celllung cancer (NSCLC) and ovarian cancer that overexpress MECP2 are alsoaddicted to continued MECP2 expression for growth, with five shRNAstested, four against coding regions, one against the 3′ UTR, with allshowing similar growth inhibition. NSCLC and ovarian cancer cell linesnot overexpressing MECP2 were not inhibited by these shRNAs.

Because MECP2 only binds to methylated CpG sequences andhydroxymethylcytosine, and because data have shown that oncogenicactivation of MECP2 depends upon its DNA-binding region, it is likelythat the oncogenic activity of MECP2 depends upon its DNA-bindingregion, it is likely that the oncogenic activity of MECP2 is mediated bybinding of the protein to methylated CpG sequences of hydroxymethylatedcytosine. For this reason, it was investigated whether DNA methylationinhibitors hinder cell growth in a MECP2-dependent manner. DNAmethylation inhibitors prevent the formation of both methylated CpGsequences and hydroxymethylated cytosine. It was shown that hMECstransformed with MECP2 are an order of magnitude more sensitive toeither of the DNA methylation inhibitors 5-azacytidine or decitabinethan are isogenic cells transformed by activated RAS, stronglysuggesting that cells transformed in a manner dependent on overexpressedMECP2 are specifically inhibited by 5-azacytidine or decitabine.

MECP2 is known to be present in a complex with Class I histonedeacetylases. It was demonstrated that the region of MECP2 required forbinding to HDACs is also required for the transformation activity ofMECP2. This led to investigation of whether MECP2-transformed cells wereparticularly vulnerable to HDAC inhibitors. MECP2-transformed cells arean order of magnitude more susceptible to the HDAC inhibitorTrichostatin A than are isogenic cells transformed by activated RAS.Furthermore, it was shown that combined treatment with the DNAmethylation inhibitor 5-azacytdine and the HDAC inhibitor Trichostatin Ais synergistic in a hMEC experimental system.

We claim:
 1. A method of treating a subject having a breast cancer, lungcancer, or ovarian cancer, wherein the cancer has an MECP2 amplificationor overexpression of MECP2, the method comprising administering to thesubject a MECP2 inhibitor, a DNA methylation inhibitor, a histonedeacetylation (HDAC) inhibitor, a MEK inhibitor, a phosphoinositide3-kinase (PI3K) inhibitor, a c-myc inhibitor, a tyrosine kinaseinhibitor or any combination thereof.
 2. The method of claim 1, whereinthe MECP2 is the long isoform and the MECP2 inhibitor is aphosphoinositide 3-kinase (PI3K) inhibitor.
 3. The method of claim 1,wherein the MECP2 is the short isoform and the MECP2 inhibitor is a MAPkinase inhibitor.
 4. The method of claim 1, further comprisingadministering to the subject a HDAC inhibitor.
 5. The method of claim 1,wherein the DNA methylation inhibitor is 5-azacytidine or decitabine. 6.The method of claim 1, wherein the DNA methylation inhibitor isadministered locally or systematically.